One Definition of Open Science

The principles of open science are to make publicly funded scientific research transparent, available, and reproducible. Advances in technology, including collaborative tools and cloud computing, help enable open science, but technology alone is insufficient. Open science requires a shift to a more transparent and collaborative scientific process, which will increase the pace and quality of scientific progress.

https://science.nasa.gov/open-science/ (accessed 2025-03-19)

Openscapes: a kinder science

Credit: Julie Lowndes and Alison Horst

Openscapes Champions: Empowering researchers by building collaborative teams.

The cloud enables open science

  • Common compute environments facilitate reproducibility
  • Streaming data accelerates workflows
  • Access to scalable computing
  • Real-time collaborative computing

Image by Alexis Hunzinger, DES DISC

Contributing to open source software

import earthaccess
import xarray as xr

earthaccess.login()

results = earthaccess.search_data(
    short_name='ATL06',  # ATLAS/ICESat-2 L3A Land Ice Height
    bounding_box=(-10, 20, 10, 50),  # Only include files in area of interest...
    temporal=("1999-02", "2019-03"),  # ...and time period of interest.
    count=10)

files = earthaccess.download(results, "/tmp/my-download-folder")

# Or 
files = earthaccess.open(results)
ds = xr.open_mfdataset(files)

Fast efficient data access

To take full advantage of the cloud we need cloud optimized data

Image Credit: https://guide.cloudnativegeo.org/

Follow Best Data Practices

Humans analyze the data but machines have to read the data. And machines are dumb, so help them out.

  • Use standard file formats
  • Common filename structures
  • Follow conventions (Tidydata, CF)
  • Include essential metadata and attributes

Open Science is a Collaborative Exercise

The Openscapes Core Team, Lowndes & Robinson (2021). Openscapes Approach Guide (Version v0.0.1). https://openscapes.org/approach-guide.